Topics & People

The projection that building the global infrastructure for AI (factories, power, networks) will require trillions of dollars in capital investment over the coming years.

Nvidia's proprietary software stack that serves as a massive strategic moat.

A high-performance GPU developed by Nvidia, used in large quantities to build AI supercomputers like xAI's Colossus.

The concept that AI is standardizing and democratizing intelligence across enterprise outputs.

A business model where a company controls multiple stages of the AI supply chain, from energy sourcing and data center construction to cloud services and operations.

A US state highlighted for having a fragile, independent electricity grid prone to failure during cold weather.

Large cloud service providers that stand to gain an oligopoly through heavy AI regulation.

The rapidly increasing demand for electricity to power AI data centers and training, which is becoming a major constraint on the growth of the AI industry.

The new foundational layer for the modern economy, comprising AI factories, energy generation, and high-speed networks necessary to power widespread AI.

A term used to reframe large-scale data centers for AI as facilities that are actively manufacturing intelligence, emphasizing their role as productive industrial assets rather than simple data processors.

A vertically integrated company that builds AI cloud infrastructure, including data centers, energy development, and application layers, with a focus on using stranded or sustainable energy sources.

CEO and co-founder of Crusoe, a company that builds and operates AI data centers powered by otherwise wasted or stranded energy sources.